A curated list of resources dedicated to Natural Language Generation (NLG), including datasets, libraries, tools, and research.
Awesome Natural Language Generation is a curated GitHub repository listing resources for Natural Language Generation (NLG). It compiles datasets, libraries, tools, research papers, and learning materials to help developers and researchers explore and implement NLG technologies for tasks like chatbots, story generation, and data description.
NLG researchers, AI/ML practitioners, data scientists, and developers building text-generation applications who need a centralized reference for tools, datasets, and state-of-the-art methods.
It saves time by aggregating scattered NLG resources into a single, well-organized list, covering both classical and neural approaches, and is maintained by the community to ensure relevance and quality.
A curated list of resources dedicated to Natural Language Generation (NLG)
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Curates a wide range of NLG resources, from datasets like WeatherGov to libraries such as Texar, saving users from scattered searches across the web.
Maintained under the Awesome list standard with community contributions, ensuring ongoing relevance and diverse perspectives, as indicated by the Awesome badge.
Spans multiple NLG domains, including dialog systems with tools like Chatito and narrative generation with Tracery, catering to varied use cases.
Includes up-to-date research papers, such as the 2022 survey on evaluation practices, supporting academic and advanced industrial projects.
The list aggregates resources without reviews or ratings, leaving users to independently evaluate the suitability and reliability of each entry.
As a manually curated list, some resources may become obsolete over time, relying on community updates which can be inconsistent.
Focuses on listing tools and papers without providing tutorials, code examples, or integration advice, making it less useful for hands-on development.